code: def motif_density(
      motif_name,
      seq_length,
      num_seqs,
      min_counts,
      max_counts,
      GC_fraction,
      central_bp=None,
  ):
      """Returns sequences with motif density, along with embeddings array."""
      import simdna
      from simdna import synthetic
  
      loaded_motifs = synthetic.LoadedEncodeMotifs(
          simdna.ENCODE_MOTIFS_PATH, pseudocountProb=0.001
      )
      substring_generator = synthetic.PwmSamplerFromLoadedMotifs(
          loaded_motifs, motif_name
      )
      if central_bp is not None:
          position_generator = synthetic.InsideCentralBp(central_bp)
      else:
          position_generator = synthetic.UniformPositionGenerator()
      quantity_generator = synthetic.UniformIntegerGenerator(
          min_counts, max_counts
      )
      embedders = [
          synthetic.RepeatedEmbedder(
              synthetic.SubstringEmbedder(
                  synthetic.ReverseComplementWrapper(
                      substring_generator
                  ),
                  position_generator,
              ),
              quantity_generator,
          )
      ]
      embed_in_background = synthetic.EmbedInABackground(
          synthetic.ZeroOrderBackgroundGenerator(
              seq_length,
              discreteDistribution=get_distribution(GC_fraction),
          ),
          embedders,
      )
      generated_sequences = tuple(
          synthetic.GenerateSequenceNTimes(
              embed_in_background, num_seqs
          ).generateSequences()
      )
      sequence_arr = np.array(
          [generated_seq.seq for generated_seq in generated_sequences]
      )
      embedding_arr = [
          generated_seq.embeddings
          for generated_seq in generated_sequences
      ]
      return sequence_arr, embedding_arr
  
file_path: deepchem/deepchem/molnet/dnasim.py
imports: import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: motif_density(motif_name, seq_length, num_seqs, min_counts, max_counts, GC_fraction, central_bp) and returns: sequence_arr,  embedding_arr